基于高性能计算的动态单光子发射计算机断层扫描成像中的稀疏域方法。
Sparse domain approaches in dynamic SPECT imaging with high-performance computing.
作者信息
Pan Hui, Chang Haoran, Mitra Debasis, Gullberg Grant T, Seo Youngho
机构信息
School of Computing, Florida Institute of TechnologyMelbourne, FL 32901, USA.
Department of Radiology and Biomedical Imaging, University of CaliforniaSan Francisco, CA 94143, USA.
出版信息
Am J Nucl Med Mol Imaging. 2017 Dec 20;7(6):283-294. eCollection 2017.
Iterative reconstruction algorithms often have relatively large computation time affecting their clinical deployment. This is especially true for 4D reconstruction in dynamic imaging (DI). In this work, we have shown how sparse domain approaches and parallelization for static 3D image reconstruction and 4D dynamic image reconstruction (directly from sinogram) in Single Photon Emission Computed Tomography (SPECT), without any intermediate 3D reconstructions, can improve computational efficiency. DI in SPECT is one of the hardest inverse problems in medical image reconstruction area and slow reconstruction is a challenge for this promising protocol. Our work hopefully, paves a new direction toward making DI in SPECT clinically viable. Our 4D reconstruction also is a novel application of non-negative matrix factorization (NNMF) in an inverse problem.
迭代重建算法通常具有较长的计算时间，这影响了它们在临床中的应用。在动态成像（DI）的4D重建中尤其如此。在这项工作中，我们展示了如何在单光子发射计算机断层扫描（SPECT）中，采用稀疏域方法和并行化技术，直接从正弦图进行静态3D图像重建和4D动态图像重建，而无需任何中间3D重建，从而提高计算效率。SPECT中的DI是医学图像重建领域中最难的逆问题之一，重建速度慢是这个有前景的协议面临的一个挑战。我们的工作有望为使SPECT中的DI在临床上可行开辟一个新方向。我们的4D重建也是非负矩阵分解（NNMF）在逆问题中的一种新应用。
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